diff --git a/svanna-cli/src/test/resources/multigene-inversion.vcf b/svanna-cli/src/test/resources/multigene-inversion.vcf
new file mode 100644
index 00000000..17786a03
--- /dev/null
+++ b/svanna-cli/src/test/resources/multigene-inversion.vcf
@@ -0,0 +1,37 @@
+##fileformat=VCFv4.2
+##fileDate=2021-01-01T00:00:00.000Z
+##INFO=<ID=SVTYPE,Number=1,Type=String,Description="Type of structural variant">
+##INFO=<ID=SVLEN,Number=.,Type=Integer,Description="Difference in length between REF and ALT alleles">
+##INFO=<ID=END,Number=1,Type=Integer,Description="End position of the structural variant described in this record">
+##INFO=<ID=CIPOS,Number=2,Type=Integer,Description="Confidence interval around POS for imprecise variants">
+##INFO=<ID=CIEND,Number=2,Type=Integer,Description="Confidence interval around END for imprecise variants">
+##INFO=<ID=IMPRECISE,Number=0,Type=Flag,Description="Imprecise structural variation">
+##FORMAT=<ID=GT,Number=1,Type=String,Description="Genotype">
+##FORMAT=<ID=AD,Number=R,Type=Integer,Description="Read depth per allele">
+##FORMAT=<ID=DP,Number=1,Type=Integer,Description="Read depth at this position for this sample">
+##contig=<ID=CM000663.2,length=248956422>
+##contig=<ID=CM000664.2,length=242193529>
+##contig=<ID=CM000665.2,length=198295559>
+##contig=<ID=CM000666.2,length=190214555>
+##contig=<ID=CM000667.2,length=181538259>
+##contig=<ID=CM000668.2,length=170805979>
+##contig=<ID=CM000669.2,length=159345973>
+##contig=<ID=CM000670.2,length=145138636>
+##contig=<ID=CM000671.2,length=138394717>
+##contig=<ID=CM000672.2,length=133797422>
+##contig=<ID=CM000673.2,length=135086622>
+##contig=<ID=CM000674.2,length=133275309>
+##contig=<ID=CM000675.2,length=114364328>
+##contig=<ID=CM000676.2,length=107043718>
+##contig=<ID=CM000677.2,length=101991189>
+##contig=<ID=CM000678.2,length=90338345>
+##contig=<ID=CM000679.2,length=83257441>
+##contig=<ID=CM000680.2,length=80373285>
+##contig=<ID=CM000681.2,length=58617616>
+##contig=<ID=CM000682.2,length=64444167>
+##contig=<ID=CM000683.2,length=46709983>
+##contig=<ID=CM000684.2,length=50818468>
+##contig=<ID=CM000685.2,length=156040895>
+##contig=<ID=CM000686.2,length=57227415>
+#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	Sample
+chr12	25803195	Something	N	<INV>	1000	PASS	SVTYPE=INV;END=125316602;SVLEN=0	GT:DP:AD	0/1:10:5,5
\ No newline at end of file
diff --git a/svanna-core/src/main/java/org/monarchinitiative/svanna/core/priority/additive/impact/GeneSequenceImpactCalculator.java b/svanna-core/src/main/java/org/monarchinitiative/svanna/core/priority/additive/impact/GeneSequenceImpactCalculator.java
index 50fe6faa..2ee3e7ae 100644
--- a/svanna-core/src/main/java/org/monarchinitiative/svanna/core/priority/additive/impact/GeneSequenceImpactCalculator.java
+++ b/svanna-core/src/main/java/org/monarchinitiative/svanna/core/priority/additive/impact/GeneSequenceImpactCalculator.java
@@ -117,7 +117,7 @@ private static List<PaddedExon> mapToPaddedExons(Transcript tx, int cdsStart, in
     @Override
     public double projectImpact(Projection<Gene> projection) {
         List<Transcript> transcripts = projection.source().transcriptStream()
-                .collect(Collectors.toUnmodifiableList());
+                .collect(Collectors.toList());
         double promoterImpact = checkPromoter(projection.route().segments(), transcripts);
 
         double geneImpact = projection.isIntraSegment()
@@ -134,15 +134,15 @@ public double noImpact() {
         return geneFactor;
     }
 
-    private double checkPromoter(List<Segment> segments, Collection<Transcript> transcripts) {
-        Set<Segment> nonGapSegments = segments.stream()
-                .filter(s -> s.event() != Event.GAP)
-                .collect(Collectors.toSet());
+    private double checkPromoter(Collection<Segment> segments, Iterable<Transcript> transcripts) {
+        Iterable<Segment> nonGapSegments = segments.stream()
+                .filter(s -> !Event.GAP.equals(s.event()))
+                .collect(Collectors.toList());
 
         double score = Double.NaN;
         for (Transcript tx : transcripts) {
             int txStart = tx.start();
-            int promoterStart = txStart - promoterLength;
+            int promoterStart = Math.max(txStart - promoterLength, 0); // Let's not allow negative start coordinate.
             int promoterEnd = txStart + Coordinates.endDelta(tx.coordinateSystem());
 
             for (Segment nonGapSegment : nonGapSegments) {
@@ -150,13 +150,27 @@ private double checkPromoter(List<Segment> segments, Collection<Transcript> tran
                 int segmentEnd = nonGapSegment.endOnStrand(tx.strand());
                 if (Coordinates.overlap(tx.coordinateSystem(), promoterStart, promoterEnd,
                         nonGapSegment.coordinateSystem(), segmentStart, segmentEnd)) {
-                    double fitness = fitnessWithEvent.get(nonGapSegment.event());
+                    double fitness;
+                    if (Event.INVERSION.equals(nonGapSegment.event())) {
+                        if (Coordinates.aContainsB(CS, segmentStart, segmentEnd, CS, promoterStart, promoterEnd))
+                            // Inversion of an entire promoter is not considered deleterious.
+                            fitness = 1;
+                        else
+                            // The promoter is disrupted by the inversion boundary, hence deleterious.
+                            fitness = fitnessWithEvent.get(Event.INVERSION);
+                    } else {
+                        // All other events are scored using default scoring scheme.
+                        fitness = fitnessWithEvent.get(nonGapSegment.event());
+                    }
+
                     // In theory, `fitness + geneFactor * promoterFitnessGain` can be above 1, which does not make sense.
                     // Let's not allow that to happen.
-                    double bla = Math.min(fitness + geneFactor * promoterFitnessGain, 1.);
-                    fitness = Math.min(bla, geneFactor);
-                    if (Double.isNaN(score) || fitness < score)
-                        score = fitness;
+                    double maxAllowedFitness = Math.min(fitness + geneFactor * promoterFitnessGain, 1.);
+                    fitness = Math.min(maxAllowedFitness, geneFactor);
+
+                    score = Double.isNaN(score)
+                            ? fitness
+                            : Math.min(fitness, score);
                 }
             }
         }